Changsoo Je | Sogang University (original) (raw)

Papers by Changsoo Je

Images often need to be aligned in a single coordinate system, and homography is one of the most ... more Images often need to be aligned in a single coordinate system, and homography is one of the most efficient geometric models to align images. This paper presents homographic p-norms, scalar metrics of homographic image transformation, and to the best of our knowledge these are the most rigorous definition of scalar metrics quantifying homographic image transformations. We first define a metric between two homography matrices, and show it satisfies metric properties. Then we propose metrics of a single homography matrix for a general planar region, and ones for a usual rectangle image. For use of the proposed metrics, we provide useful homographic 2-norm expressions derived from the definition of the metrics, and compare the approximation errors of the metrics with respect to the exact metric. As a result, the discrete version of the metric obtained by pixel-wise computation is greatly close to the exact metric. The proposed metrics can be applied to evaluation of transformation magnitude, image closeness estimation, evaluation of camera pose difference, selection of image pair in stereo vision, panoramic image mosaic, and deblurring. Experimental results show the efficacy of the proposed metrics.

We propose a novel reflection color model consisting of body essence and (mixed) neuter, and pres... more We propose a novel reflection color model consisting of body essence and (mixed) neuter, and present an effective method for separating dichromatic reflection components using a single image. Body essence is an entity invariant to interface reflection, and has two degrees of freedom unlike hue and maximum chromaticity. As a result, the proposed method is insensitive to noise and proper for colors around CMY (cyan, magenta, and yellow) as well as RGB (red, green, and blue), contrary to the maximum chromaticity-based methods. Interface reflection is separated by using a Gaussian function, which removes a critical thresholding problem. Furthermore, the method does not require any region segmentation. Experimental results show the efficacy of the proposed model and method.

In computer vision, two major active range imaging methods have been frequently employed for rapi... more In computer vision, two major active range imaging methods have been frequently employed for rapid and efficient shape recovery: (a) conventional active stereo vision and (b) conventional structured-light vision. This paper presents a comparative analysis and an integration of the two active approaches, namely, a structured-light stereo approach for the acquisition of dynamic shape. We first investigate the strengths and weaknesses of the two approaches in terms of accuracy, computational cost, field of view, depth of field, and color sensitivity. Based on this analysis, we propose a novel integrated method, the structured-light stereo, to recover dynamic shapes from a wider view with less occlusion by taking most of the benefits of the two approaches. The main idea is as follows. We first build a system composed of two cameras and a single projector (just a basic setup for conventional active stereo), and the projector projects a single “one-shot” color-stripe pattern. The next step is to estimate reliable correspondences between each camera and the projector via an accurate and efficient pattern decoding technique, and some remaining unresolved regions are explored by a stereo matching technique, which is less sensitive to object surface colors and defocus due to the projector's short depth of field, to estimate additional correspondences. We demonstrate the efficacy of the integrated method through experimental results.

Research interest in rapid structured-light imaging has grown increasingly for the modeling of mo... more Research interest in rapid structured-light imaging has grown increasingly for the modeling of moving objects, and a number of methods have been suggested for the range capture in a single video frame. The imaging area of a 3D object using a single projector is restricted since the structured light is projected only onto a limited area of the object surface. Employing additional projectors to broaden the imaging area is a challenging problem since simultaneous projection of multiple patterns results in their superposition in the light-intersected areas and the recognition of original patterns is by no means trivial. This paper presents a novel method of multi-projector color structured-light vision based on projector–camera triangulation. By analyzing the behavior of superposed-light colors in a chromaticity domain, we show that the original light colors cannot be properly extracted by the conventional direct estimation. We disambiguate multiple projectors by multiplexing the orientations of projector patterns so that the superposed patterns can be separated by explicit derivative computations. Experimental studies are carried out to demonstrate the validity of the presented method. The proposed method increases the efficiency of range acquisition compared to conventional active stereo using multiple projectors.

Obtaining a good-quality image requires exposure to light for an appropriate amount of time. If t... more Obtaining a good-quality image requires exposure to light for an appropriate amount of time. If there is camera or object motion during the exposure time, the image is blurred. To remove the blur, some recent image deblurring methods effectively estimate a point spread function (PSF) by acquiring a noisy image additionally, and restore a clear latent image with the PSF. Since the groundtruth PSF varies with the location, a blockwise approach for PSF estimation has been proposed. However, the block to estimate a PSF is a straightly demarcated rectangle which is generally different from the shape of an actual region where the PSF can be properly assumed constant. We utilize the fact that a PSF is substantially related to the local disparity between two views. This paper presents a disparity-based method of space-variant image deblurring which employs disparity information in image segmentation, and estimates a PSF, and restores a latent image for each region. The segmentation method firstly over-segments a blurred image into sufficiently many regions based on color, and then merges adjacent regions with similar disparities. Experimental results show the effectiveness of the proposed method.

Recently the camera resolution has been highly increased, and the registration between high-resol... more Recently the camera resolution has been highly increased, and the registration between high-resolution images is computationally expensive even by using hierarchical block matching. This paper presents a novel optimized hierarchical block matching algorithm in which the computational cost is minimized for the scale factor and the number of levels in the hierarchy. The algorithm is based on a generalized version of the Gaussian pyramid and its inter-layer transformation of coordinates. The search window size is properly determined to resolve possible error propagation in hierarchical block matching. In addition, we also propose a simple but effective method for aligning colors between two images based on color distribution adjustment as a preprocessing. Simplifying a general color imaging model, we show much of the color inconsistency can be compensated by our color alignment method. The experimental results show that the optimized hierarchical block matching and color alignment methods increase the block matching speed and accuracy, and thus improve image registration. Using our algorithm, it takes about 1.28 s for overall registration process with a pair of images in 5 mega-pixel resolution.

Proc. 11th Asian Conference on Computer Vision (ACCV 2012), Special Session: RGB-D (Xbox-Kinect) Application Competition, Nov 6, 2012

For structured-light range imaging, colour stripes can be used for increasing the number of disti... more For structured-light range imaging, colour stripes can be used for increasing the number of distinguishable light patterns compared to binary black-and-white stripes. Therefore, an appropriate use of colour patterns can reduce the number of required light projections for imaging an object scene, and range imaging can be achievable in a single video frame or in “one-shot”. On the other hand, the reliability and range resolution attainable from colour stripes are generally lower than those from temporally encoded binary black-and-white patterns since colour contrast is affected by object colour reflectance and ambient light. This paper presents new methods for selecting stripe colours and designing multiple-stripe patterns for “one-shot” and “two-shot” imaging. We show that maximizing colour contrast between the stripes in one-shot imaging reduces the ambiguities resulting from coloured object surfaces and limitations in sensor/projector resolution. Moreover, a cross-stripe gradient method is presented to improve estimation of illumination patterns in one-shot imaging. Two-shot imaging adds an extra video frame and maximizes the colour contrast between the first and second video frames to diminish the ambiguities even further. Experimental results and discussion demonstrate the effectiveness and robustness of the presented one-shot and two-shot colour-stripe imaging schemes.

We present a real-time algorithm that finds the Penetration Depth (PD) between general polygonal ... more We present a real-time algorithm that finds the Penetration Depth (PD) between general polygonal models based on iterative and local optimization techniques. Given an in-collision configuration of an object in configuration space, we find an initial collision-free configuration using several methods such as centroid difference, maximally clear configuration, motion coherence, random configuration, and sampling-based search. We project this configuration on to a local contact space using a variant of continuous collision detection algorithm and construct a linear convex cone around the projected configuration. We then formulate a new projection of the in-collision configuration onto the convex cone as a Linear Complementarity Problem (LCP), which we solve using a type of Gauss-Seidel iterative algorithm. We repeat this procedure until a locally optimal PD is obtained. Our algorithm can process complicated models consisting of tens of thousands triangles at interactive rates.

Computer Vision - ACCV 2007, LNCS 4844, Nov 14, 2007

Multiple color stripes have been employed for structured light-based rapid range imaging to incre... more Multiple color stripes have been employed for structured light-based rapid range imaging to increase the number of uniquely identifiable stripes. The use of multiple color stripes poses two problems: (1) object surface color may disturb the stripe color and (2) the number of adjacent stripes required for identifying a stripe may not be maintained near surface discontinuities such as occluding boundaries. In this paper, we present methods to alleviate those problems. Log-gradient filters are employed to reduce the influence of object colors, and color stripes in two and three directions are used to increase the chance of identifying correct stripes near surface discontinuities. Experimental results demonstrate the effectiveness of our methods.

Computer Vision – ECCV 2004, LNCS 3021, May 10, 2004

For structured-light range imaging, color stripes can be used for increasing the number of distin... more For structured-light range imaging, color stripes can be used for increasing the number of distinguishable light patterns compared to binary BW stripes. Therefore, an appropriate use of color patterns can reduce the number of light projections and range imaging is achievable in single video frame or in “one shot”. On the other hand, the reliability and range resolution attainable from color stripes is generally lower than those from multiply projected binary BW patterns since color contrast is affected by object color reflectance and ambient light. This paper presents new methods for selecting stripe colors and designing multiple-stripe patterns for “one-shot” and “two-shot” imaging. We show that maximizing color contrast between the stripes in one-shot imaging reduces the ambiguities resulting from colored object surfaces and limitations in sensor/projector resolution. Two-shot imaging adds an extra video frame and maximizes the color contrast between the first and second video frames to diminish the ambiguities even further. Experimental results demonstrate the effectiveness of the presented one-shot and two-shot color-stripe imaging schemes.

Proc. 6th Asian Conference on Computer Vision (ACCV 2004), Jan 27, 2004

Active range sensing using structured-light is the most accurate and reliable method for obtainin... more Active range sensing using structured-light is the most accurate and reliable method for obtaining 3D information. However, most of the work has been limited to range sensing of static objects, and range sensing of dynamic (moving or deforming) objects has been investigated recently only by a few researchers. Sinusoidal structured-light is one of the well-known optical methods for 3D measurement. In this paper, we present a novel method for rapid high-resolution range imaging using color sinusoidal pattern. We consider the real-world problem of nonlinearity and color-band crosstalk in the color light projector and color camera, and present methods for accurate recovery of color-phase. For high-resolution ranging, we use high-frequency patterns and describe new unwrapping algorithms for reliable range recovery. The experimental results demonstrate the effectiveness of our methods.

Images often need to be aligned in a single coordinate system, and homography is one of the most ... more Images often need to be aligned in a single coordinate system, and homography is one of the most efficient geometric models to align images. This paper presents homographic p-norms, scalar metrics of homographic image transformation, and to the best of our knowledge these are the most rigorous definition of scalar metrics quantifying homographic image transformations. We first define a metric between two homography matrices, and show it satisfies metric properties. Then we propose metrics of a single homography matrix for a general planar region, and ones for a usual rectangle image. For use of the proposed metrics, we provide useful homographic 2-norm expressions derived from the definition of the metrics, and compare the approximation errors of the metrics with respect to the exact metric. As a result, the discrete version of the metric obtained by pixel-wise computation is greatly close to the exact metric. The proposed metrics can be applied to evaluation of transformation magnitude, image closeness estimation, evaluation of camera pose difference, selection of image pair in stereo vision, panoramic image mosaic, and deblurring. Experimental results show the efficacy of the proposed metrics.

We propose a novel reflection color model consisting of body essence and (mixed) neuter, and pres... more We propose a novel reflection color model consisting of body essence and (mixed) neuter, and present an effective method for separating dichromatic reflection components using a single image. Body essence is an entity invariant to interface reflection, and has two degrees of freedom unlike hue and maximum chromaticity. As a result, the proposed method is insensitive to noise and proper for colors around CMY (cyan, magenta, and yellow) as well as RGB (red, green, and blue), contrary to the maximum chromaticity-based methods. Interface reflection is separated by using a Gaussian function, which removes a critical thresholding problem. Furthermore, the method does not require any region segmentation. Experimental results show the efficacy of the proposed model and method.

In computer vision, two major active range imaging methods have been frequently employed for rapi... more In computer vision, two major active range imaging methods have been frequently employed for rapid and efficient shape recovery: (a) conventional active stereo vision and (b) conventional structured-light vision. This paper presents a comparative analysis and an integration of the two active approaches, namely, a structured-light stereo approach for the acquisition of dynamic shape. We first investigate the strengths and weaknesses of the two approaches in terms of accuracy, computational cost, field of view, depth of field, and color sensitivity. Based on this analysis, we propose a novel integrated method, the structured-light stereo, to recover dynamic shapes from a wider view with less occlusion by taking most of the benefits of the two approaches. The main idea is as follows. We first build a system composed of two cameras and a single projector (just a basic setup for conventional active stereo), and the projector projects a single “one-shot” color-stripe pattern. The next step is to estimate reliable correspondences between each camera and the projector via an accurate and efficient pattern decoding technique, and some remaining unresolved regions are explored by a stereo matching technique, which is less sensitive to object surface colors and defocus due to the projector's short depth of field, to estimate additional correspondences. We demonstrate the efficacy of the integrated method through experimental results.

Research interest in rapid structured-light imaging has grown increasingly for the modeling of mo... more Research interest in rapid structured-light imaging has grown increasingly for the modeling of moving objects, and a number of methods have been suggested for the range capture in a single video frame. The imaging area of a 3D object using a single projector is restricted since the structured light is projected only onto a limited area of the object surface. Employing additional projectors to broaden the imaging area is a challenging problem since simultaneous projection of multiple patterns results in their superposition in the light-intersected areas and the recognition of original patterns is by no means trivial. This paper presents a novel method of multi-projector color structured-light vision based on projector–camera triangulation. By analyzing the behavior of superposed-light colors in a chromaticity domain, we show that the original light colors cannot be properly extracted by the conventional direct estimation. We disambiguate multiple projectors by multiplexing the orientations of projector patterns so that the superposed patterns can be separated by explicit derivative computations. Experimental studies are carried out to demonstrate the validity of the presented method. The proposed method increases the efficiency of range acquisition compared to conventional active stereo using multiple projectors.

Obtaining a good-quality image requires exposure to light for an appropriate amount of time. If t... more Obtaining a good-quality image requires exposure to light for an appropriate amount of time. If there is camera or object motion during the exposure time, the image is blurred. To remove the blur, some recent image deblurring methods effectively estimate a point spread function (PSF) by acquiring a noisy image additionally, and restore a clear latent image with the PSF. Since the groundtruth PSF varies with the location, a blockwise approach for PSF estimation has been proposed. However, the block to estimate a PSF is a straightly demarcated rectangle which is generally different from the shape of an actual region where the PSF can be properly assumed constant. We utilize the fact that a PSF is substantially related to the local disparity between two views. This paper presents a disparity-based method of space-variant image deblurring which employs disparity information in image segmentation, and estimates a PSF, and restores a latent image for each region. The segmentation method firstly over-segments a blurred image into sufficiently many regions based on color, and then merges adjacent regions with similar disparities. Experimental results show the effectiveness of the proposed method.

Recently the camera resolution has been highly increased, and the registration between high-resol... more Recently the camera resolution has been highly increased, and the registration between high-resolution images is computationally expensive even by using hierarchical block matching. This paper presents a novel optimized hierarchical block matching algorithm in which the computational cost is minimized for the scale factor and the number of levels in the hierarchy. The algorithm is based on a generalized version of the Gaussian pyramid and its inter-layer transformation of coordinates. The search window size is properly determined to resolve possible error propagation in hierarchical block matching. In addition, we also propose a simple but effective method for aligning colors between two images based on color distribution adjustment as a preprocessing. Simplifying a general color imaging model, we show much of the color inconsistency can be compensated by our color alignment method. The experimental results show that the optimized hierarchical block matching and color alignment methods increase the block matching speed and accuracy, and thus improve image registration. Using our algorithm, it takes about 1.28 s for overall registration process with a pair of images in 5 mega-pixel resolution.

Proc. 11th Asian Conference on Computer Vision (ACCV 2012), Special Session: RGB-D (Xbox-Kinect) Application Competition, Nov 6, 2012

For structured-light range imaging, colour stripes can be used for increasing the number of disti... more For structured-light range imaging, colour stripes can be used for increasing the number of distinguishable light patterns compared to binary black-and-white stripes. Therefore, an appropriate use of colour patterns can reduce the number of required light projections for imaging an object scene, and range imaging can be achievable in a single video frame or in “one-shot”. On the other hand, the reliability and range resolution attainable from colour stripes are generally lower than those from temporally encoded binary black-and-white patterns since colour contrast is affected by object colour reflectance and ambient light. This paper presents new methods for selecting stripe colours and designing multiple-stripe patterns for “one-shot” and “two-shot” imaging. We show that maximizing colour contrast between the stripes in one-shot imaging reduces the ambiguities resulting from coloured object surfaces and limitations in sensor/projector resolution. Moreover, a cross-stripe gradient method is presented to improve estimation of illumination patterns in one-shot imaging. Two-shot imaging adds an extra video frame and maximizes the colour contrast between the first and second video frames to diminish the ambiguities even further. Experimental results and discussion demonstrate the effectiveness and robustness of the presented one-shot and two-shot colour-stripe imaging schemes.

We present a real-time algorithm that finds the Penetration Depth (PD) between general polygonal ... more We present a real-time algorithm that finds the Penetration Depth (PD) between general polygonal models based on iterative and local optimization techniques. Given an in-collision configuration of an object in configuration space, we find an initial collision-free configuration using several methods such as centroid difference, maximally clear configuration, motion coherence, random configuration, and sampling-based search. We project this configuration on to a local contact space using a variant of continuous collision detection algorithm and construct a linear convex cone around the projected configuration. We then formulate a new projection of the in-collision configuration onto the convex cone as a Linear Complementarity Problem (LCP), which we solve using a type of Gauss-Seidel iterative algorithm. We repeat this procedure until a locally optimal PD is obtained. Our algorithm can process complicated models consisting of tens of thousands triangles at interactive rates.

Computer Vision - ACCV 2007, LNCS 4844, Nov 14, 2007

Multiple color stripes have been employed for structured light-based rapid range imaging to incre... more Multiple color stripes have been employed for structured light-based rapid range imaging to increase the number of uniquely identifiable stripes. The use of multiple color stripes poses two problems: (1) object surface color may disturb the stripe color and (2) the number of adjacent stripes required for identifying a stripe may not be maintained near surface discontinuities such as occluding boundaries. In this paper, we present methods to alleviate those problems. Log-gradient filters are employed to reduce the influence of object colors, and color stripes in two and three directions are used to increase the chance of identifying correct stripes near surface discontinuities. Experimental results demonstrate the effectiveness of our methods.

Computer Vision – ECCV 2004, LNCS 3021, May 10, 2004

For structured-light range imaging, color stripes can be used for increasing the number of distin... more For structured-light range imaging, color stripes can be used for increasing the number of distinguishable light patterns compared to binary BW stripes. Therefore, an appropriate use of color patterns can reduce the number of light projections and range imaging is achievable in single video frame or in “one shot”. On the other hand, the reliability and range resolution attainable from color stripes is generally lower than those from multiply projected binary BW patterns since color contrast is affected by object color reflectance and ambient light. This paper presents new methods for selecting stripe colors and designing multiple-stripe patterns for “one-shot” and “two-shot” imaging. We show that maximizing color contrast between the stripes in one-shot imaging reduces the ambiguities resulting from colored object surfaces and limitations in sensor/projector resolution. Two-shot imaging adds an extra video frame and maximizes the color contrast between the first and second video frames to diminish the ambiguities even further. Experimental results demonstrate the effectiveness of the presented one-shot and two-shot color-stripe imaging schemes.

Proc. 6th Asian Conference on Computer Vision (ACCV 2004), Jan 27, 2004

Active range sensing using structured-light is the most accurate and reliable method for obtainin... more Active range sensing using structured-light is the most accurate and reliable method for obtaining 3D information. However, most of the work has been limited to range sensing of static objects, and range sensing of dynamic (moving or deforming) objects has been investigated recently only by a few researchers. Sinusoidal structured-light is one of the well-known optical methods for 3D measurement. In this paper, we present a novel method for rapid high-resolution range imaging using color sinusoidal pattern. We consider the real-world problem of nonlinearity and color-band crosstalk in the color light projector and color camera, and present methods for accurate recovery of color-phase. For high-resolution ranging, we use high-frequency patterns and describe new unwrapping algorithms for reliable range recovery. The experimental results demonstrate the effectiveness of our methods.